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Data-driven classification of patients with primary progressive aphasia
Current diagnostic criteria classify primary progressive aphasia into three variants–semantic (sv), nonfluent (nfv) and logopenic (lv) PPA–though the adequacy of this scheme is debated. This study took a data-driven approach, applying k-means clustering to data from 43 PPA patients. The algorithm gr...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5626563/ https://www.ncbi.nlm.nih.gov/pubmed/28803212 http://dx.doi.org/10.1016/j.bandl.2017.08.001 |
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author | Hoffman, Paul Sajjadi, Seyed Ahmad Patterson, Karalyn Nestor, Peter J. |
author_facet | Hoffman, Paul Sajjadi, Seyed Ahmad Patterson, Karalyn Nestor, Peter J. |
author_sort | Hoffman, Paul |
collection | PubMed |
description | Current diagnostic criteria classify primary progressive aphasia into three variants–semantic (sv), nonfluent (nfv) and logopenic (lv) PPA–though the adequacy of this scheme is debated. This study took a data-driven approach, applying k-means clustering to data from 43 PPA patients. The algorithm grouped patients based on similarities in language, semantic and non-linguistic cognitive scores. The optimum solution consisted of three groups. One group, almost exclusively those diagnosed as svPPA, displayed a selective semantic impairment. A second cluster, with impairments to speech production, repetition and syntactic processing, contained a majority of patients with nfvPPA but also some lvPPA patients. The final group exhibited more severe deficits to speech, repetition and syntax as well as semantic and other cognitive deficits. These results suggest that, amongst cases of non-semantic PPA, differentiation mainly reflects overall degree of language/cognitive impairment. The observed patterns were scarcely affected by inclusion/exclusion of non-linguistic cognitive scores. |
format | Online Article Text |
id | pubmed-5626563 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-56265632017-11-01 Data-driven classification of patients with primary progressive aphasia Hoffman, Paul Sajjadi, Seyed Ahmad Patterson, Karalyn Nestor, Peter J. Brain Lang Article Current diagnostic criteria classify primary progressive aphasia into three variants–semantic (sv), nonfluent (nfv) and logopenic (lv) PPA–though the adequacy of this scheme is debated. This study took a data-driven approach, applying k-means clustering to data from 43 PPA patients. The algorithm grouped patients based on similarities in language, semantic and non-linguistic cognitive scores. The optimum solution consisted of three groups. One group, almost exclusively those diagnosed as svPPA, displayed a selective semantic impairment. A second cluster, with impairments to speech production, repetition and syntactic processing, contained a majority of patients with nfvPPA but also some lvPPA patients. The final group exhibited more severe deficits to speech, repetition and syntax as well as semantic and other cognitive deficits. These results suggest that, amongst cases of non-semantic PPA, differentiation mainly reflects overall degree of language/cognitive impairment. The observed patterns were scarcely affected by inclusion/exclusion of non-linguistic cognitive scores. Elsevier 2017-11 /pmc/articles/PMC5626563/ /pubmed/28803212 http://dx.doi.org/10.1016/j.bandl.2017.08.001 Text en © 2017 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Hoffman, Paul Sajjadi, Seyed Ahmad Patterson, Karalyn Nestor, Peter J. Data-driven classification of patients with primary progressive aphasia |
title | Data-driven classification of patients with primary progressive aphasia |
title_full | Data-driven classification of patients with primary progressive aphasia |
title_fullStr | Data-driven classification of patients with primary progressive aphasia |
title_full_unstemmed | Data-driven classification of patients with primary progressive aphasia |
title_short | Data-driven classification of patients with primary progressive aphasia |
title_sort | data-driven classification of patients with primary progressive aphasia |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5626563/ https://www.ncbi.nlm.nih.gov/pubmed/28803212 http://dx.doi.org/10.1016/j.bandl.2017.08.001 |
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